Facilitation of determination of antenna location

ABSTRACT

Assisted global positioning system (AGPS) information is retrieved from mobile devices and employed to facilitate antenna location. Measurement information, including AGPS information, can be received from a plurality of mobile devices dispersed over a geographical region. The measurement information can include location and timing information for the plurality of mobile devices. A timing difference between co-located antennas of a base station associated with the plurality of mobile devices can be computed. The location of the co-located antennas can be determined based on evaluating errors resultant from estimations based on a plurality of test locations. The measurement information can be aggregated over time and can be employed to update the antenna locations.

TECHNICAL FIELD

The subject disclosure relates to wireless communications and, moreparticularly, to various embodiments that facilitate determination ofantenna location within wireless communications networks.

BACKGROUND

Accurate antenna location information can enable a wirelesscommunications system to provide locating systems and location-basedservices that rely on antenna location information. For example,location-based services that aide parents in locating children viahandset location can be provided. Further, accurate antenna locationinformation can also benefit network modeling tools that rely on antennalocation information to accurately model signal coverage. As antennalocations change on a tower or rooftop, antenna location information canbe determined and employed to adjust network modeling tools for improvedconsistent accuracy.

SUMMARY

The following presents a simplified summary of one or more of theembodiments in order to provide a basic understanding of someembodiments of the embodiments. This summary is not an extensiveoverview of the embodiments described herein. It is intended to neitheridentify key or critical elements of the embodiments nor delineate anyscope particular embodiments of the embodiments or any scope of theclaims. Its sole purpose is to present some concepts of the embodimentsin a simplified form as a prelude to the more detailed description thatis presented later. It will also be appreciated that the detaileddescription may include additional or alternative embodiments beyondthose described in this summary.

In one embodiment, a method can include: collecting, by a systemincluding at least one processor, measurement information from aplurality of mobile devices dispersed over a geographical region,wherein the measurement information includes location and timinginformation for the plurality of mobile devices; computing, by thesystem, a timing difference between co-located antennas of a basestation associated with the plurality of mobile devices; anddetermining, by the system, a location of a first one of the co-locatedantennas and a location of a second one of the co-located antennas,based, at least, on a plurality of test locations of the second one ofthe co-located antennas and errors associated with the plurality of testlocations.

In one embodiment, a non-transitory computer-readable storage medium caninclude computer-executable instructions that, in response to execution,cause a system including a processor to perform operations. Theoperations can include: receiving measurement information from aplurality of mobile devices, wherein the measurement informationcomprises assisted global positioning system information; anddetermining at least one estimated base station antenna location based,at least, on the measurement information.

In one embodiment, a system can include: a memory that storescomputer-executable instructions; and a processor, communicativelycoupled to the memory, that facilitates execution of computer-executableinstructions to at least: determine information from a plurality ofmobile devices; and select ones of the plurality of mobile devices toquery for assisted global positioning system information based, atleast, on a set of criteria, wherein the set of criteria comprise afirst criterion based on whether the plurality of mobile devices have ahistorical active call duration within a predetermined range of time,and a second criterion based on whether the plurality of mobile devicesare configured with assisted global positioning system capability.

The following description and the annexed drawings set forth certainillustrative embodiments of the embodiments. These embodiments areindicative, however, of but a few of the various ways in which theprinciples of the embodiments can be employed. Other features of theembodiments will become apparent from the following detailed descriptionof the embodiments when considered in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system that facilitates determination ofantenna location.

FIG. 2 illustrates an example system that can be employed to facilitatedetermination of antenna location.

FIG. 3 illustrates another example system that can be employed tofacilitate determination of antenna location.

FIG. 4 illustrates an example data storage that facilitatesdetermination of antenna location.

FIGS. 5-9 illustrate example flowcharts of methods that facilitatedetermination of antenna location.

FIG. 10 illustrates a block diagram of a computer operable to facilitatedetermination of antenna location.

DETAILED DESCRIPTION

One or more embodiments are now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the various embodiments. It is evident,however, that the various embodiments can be practiced without thesespecific details (and without applying to any particular networkedenvironment or standard).

As used in this application, the terms “component,” “module,” “system,”“interface,” “platform,” “service,” “framework,” “connector,”“controller” or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software or software in execution or an entity related to anoperational machine with one or more specific functionalities. Forexample, a component can be, but is not limited to being, a processrunning on a processor, a processor, an object, an executable, a threadof execution, a program, and/or a computer. By way of illustration, bothan application running on a controller and the controller can be acomponent. One or more components can reside within a process and/orthread of execution and a component can be localized on one computerand/or distributed between two or more computers. As another example, aninterface can include input/output (I/O) components as well asassociated processor, application, and/or application programminginterface (API) components.

Further, the various embodiments can be implemented as a method,apparatus or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device or computer-readable storage/communicationsmedia. For example, computer readable storage media can include, but arenot limited to, magnetic storage devices (e.g., hard disk, floppy disk,magnetic strips), optical disks (e.g., compact disk (CD), digitalversatile disk (DVD)), smart cards, and flash memory devices (e.g.,card, stick, key drive). Of course, those skilled in the art willrecognize many modifications can be made to this configuration withoutdeparting from the scope or spirit of the various embodiments.

In addition, the words “example” and “exemplary” are used herein to meanserving as an instance or illustration. Any embodiment or designdescribed herein as “example” or “exemplary” is not necessarily to beconstrued as preferred or advantageous over other embodiments ordesigns. Rather, use of the word example or exemplary is intended topresent concepts in a concrete fashion. As used in this application, theterm “or” is intended to mean an inclusive “or” rather than an exclusive“or”. That is, unless specified otherwise or clear from context, “Xemploys A or B” is intended to mean any of the natural inclusivepermutations. That is, if X employs A; X employs B; or X employs both Aand B, then “X employs A or B” is satisfied under any of the foregoinginstances. In addition, the articles “a” and “an” as used in thisapplication and the appended claims should generally be construed tomean “one or more” unless specified otherwise or clear from context tobe directed to a singular form.

Moreover, terms such as “user equipment,” “mobile station,” “mobile,”subscriber station,” “access terminal,” “terminal,” “handset,” “mobiledevice” (and/or terms representing similar terminology) can refer to awireless device utilized by a subscriber or user of a wirelesscommunication service to receive or convey data, control, voice, video,sound, gaming or substantially any data-stream or signaling-stream. Theforegoing terms are utilized interchangeably herein and with referenceto the related drawings. Likewise, the terms “access point (AP),” “basestation (BS),” “Node B,” “evolved Node B (eNode B),” “home Node B (HNB)”and the like, are utilized interchangeably in the application, and referto a wireless network component or appliance that transmits and/orreceives data, control, voice, video, sound, gaming or substantially anydata-stream or signaling-stream from one or more subscriber stations.Data and signaling streams can be packetized or frame-based flows.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer” andthe like are employed interchangeably throughout, unless contextwarrants particular distinctions among the terms. It should beappreciated that such terms can refer to human entities or automatedcomponents supported through artificial intelligence (e.g., a capacityto make inference based, at least, on complex mathematical formalisms),which can provide simulated vision, sound recognition and so forth.

Embodiments described herein can be exploited in substantially anywireless communication technology, including, but not limited to,Wireless Fidelity (Wi-Fi), Global System for Mobile Communications(GSM), Universal Mobile Telecommunications System (UMTS), WorldwideInteroperability for Microwave Access (WiMAX), Enhanced General PacketRadio Service (Enhanced GPRS), Third Generation Partnership Project(3GPP) Long Term Evolution (LTE), Third Generation Partnership Project 2(3GPP2) Ultra Mobile Broadband (UMB), High Speed Packet Access (HSPA),Zigbee and other 802.XX wireless technologies and/or legacytelecommunication technologies. Further, the term “femto” and“femtocell” are used interchangeably, and the terms “macro” and“macrocell” are used interchangeably.

Various embodiments described herein relate to efficient use of assistedglobal positioning system (AGPS) information retrieval yield, anddetermination of antenna locations using AGPS information. One or moreof the embodiments can identify particular mobile terminals, and/orsubscribers associated with such mobile terminals, to target forretrieval of AGPS information. Further, the AGPS information can beemployed to estimate antenna locations within a wireless communicationnetwork.

One or more of the embodiments can improve upon previous approaches ofmanually recording antenna locations by employing aggregatedmeasurements from AGPS information retrieved from mobile terminalswithin a coverage area of a particular wireless network. In particular,measurement information can be retrieved from the IuB interfaces of aset of mobile terminals and aggregated over time. Statistical approachescan be employed to identify the geographic locations of one or moreantennas contributing to the set of mobile terminals.

One or more of the embodiments can provide automatic methods tofacilitate validation or invalidation of antenna location informationinput into databases parameters. Such embodiments can lead to specificinvestigations of the entries and/or corrections of those values,instrumentation or methods.

One or more embodiments can improve database accuracy, which can improvelocating systems, internal and/or external, that rely on antennalocation information. One or more embodiments can also benefit networkmodeling tools that rely on accurate antenna placement to accuratelymodel signal coverage. One or more embodiments can improve differenttypes of Location-Based Services (LBS) (e.g., services that aide parentsin locating children via handset location).

FIG. 1 illustrates an example system that facilitates determination ofantenna location. System 100 can include a cell 104 associated withco-located antennas 106, 107 co-located antennas 106, 107, mobiledevices 108, 110, 112, 114 and/or an antenna location determinationsystem 116. In some embodiments, the co-located antennas 106, 107 can beassociated with a BS (not shown) and/or can be positioned on a building(e.g., building 102) within the cell 104. In one or more embodiments,the co-located antennas 106, 107, mobile devices 108, 110, 112, 114and/or an antenna location determination system 116 can be electricallyand/or communicatively coupled to one another to perform one or morefunctions of system 100.

The co-located antennas 106, 107 can transmit and/or receive informationto and/or from the antenna location determination system 116 and/or themobile devices 108, 110, 112, 114.

The mobile devices 108, 110, 112, 114 can be configured with assistedglobal positioning system (AGPS) capability and can transmit and/orreceive AGPS information to or from the antenna location determinationsystem 116 and/or the co-located antennas 106, 107. In variousembodiments, the AGPS information can include, but is not limited to,location and timing information for the mobile devices 108, 110, 112,114. The location and/or timing information can be employed to determineantenna locations for co-located antennas serving the mobile devices108, 110, 112, 114.

The antenna location determination system 116 can determine an estimatedlocation for the co-located antennas 106, 107. In various embodiments,the antenna location determination system 116 can receive informationfrom and transmit information to the mobile devices 108, 110, 112, 114.For example, in some embodiments, the antenna location determinationsystem 116 can receive AGPS information from one or more of the mobiledevices 108, 110, 112, 114.

The antenna location determination system 116 will now be described inmore detail with reference to the remaining figures. Turning first toFIG. 2, FIG. 2 illustrates an example antenna location determinationsystem 116′ that can be employed to facilitate determination of antennalocation. The antenna location determination system 116′ can include oneor more of the structure and/or functionality of the antenna locationdetermination system 116 described with reference to FIG. 1 (and viceversa).

Turning first to FIG. 2, the antenna location determination system 116′can include a communication component 200, an aggregation component 202,a computation component 204, a memory 206, a processor 208 and/or datastorage 210. In one or more embodiments, the communication component200, aggregation component 202, computation component 204, memory 206,processor 208 and/or data storage 210 can be electrically and/orcommunicatively coupled to one another to perform one or more of thefunctions of the antenna location determination system 116′.

The communication component 200 can transmit information to and/orreceive information from one or more mobile devices and/or theco-located antennas. The information can be measurement information(e.g., AGPS information), information regarding an estimated antennalocation, data, voice, video and/or a combination of one or more of theabove types of information.

In some embodiments, the communication component 200 can selectparticular mobile devices from which to solicit information (e.g., AGPSinformation). The mobile devices selected by the communication component200 can be associated with the same co-located antennas in variousembodiments.

In various embodiments, the communication component 200 can communicatewith selected pairs of the mobile devices to obtain information forantenna location. By way of example, but not limitation, with referenceto FIG. 1, mobile devices 108, 110 can be selected as a first pair ofmobile devices from which AGPS information is to be received, and mobiledevices 112, 114 can be selected as a second pair of mobile devices fromwhich AGPS information is to be received. The information from each paircan be aggregated and employed in the determination of an estimatedantenna location.

In various embodiments, the AGPS information can be received by thecommunication component 200 in response to the communication component200 transmitting one or more AGPS queries to one or more mobile devices.

In some embodiments, the communication component 200 can determine theone or more mobile devices to query for AGPS information. The selectionof mobile devices to solicit for AGPS information can be made based onwhether the mobile devices meet a particular criterion.

In some embodiments, the mobile devices selected can be those meeting afundamental set of criteria. In some embodiments, the fundamentalcriteria can be association with a particular subscriber, having AGPScapability, currently active and/or having a historical telephone callduration within a predetermined range of time.

Specifically, the one or more mobile devices that have an active calltime duration within a particular range of time can be selected. Forexample, one or more mobile devices having a history of having an activecall time duration between approximately 10 and 40 seconds can beselected for solicitation of AGPS information.

In some embodiments, mobile devices having a history of active callswith a duration beyond 10 seconds tend to continue longer than a typicalshort duration call while active calls having a duration of at least 40seconds are likely to expire prior to receiving a response from the AGPSrequest, which can take approximately 20 to 30 seconds from time ofrequest.

In some embodiments, the one or more mobile devices selected by thecommunication component 200 can be those meeting the fundamental set ofcriteria, and also reporting a current signal strength of at least apredetermined value. For example, in some embodiments, the one or moremobile devices selected can be those reporting a current signal strengthbetween −90 dBm and −45 dBm.

In some embodiments, the one or more mobile devices selected by thecommunication component 200 can be those meeting the fundamental set ofcriteria, and also reporting at least a predetermined number of TMvalues in the radio resource control (RRC) measurement report. In someembodiments, the mobile devices selected can be those reporting thehighest TM value in the RRC measurement report.

In some embodiments, the one or more mobile devices selected by thecommunication component 200 can be those meeting the fundamental set ofcriteria, and those currently in a selected area of a network. Forexample, an area of a network can be selected based, at least, on ahistorical yield of successful responses to the AGPS request that meetsor exceeds a particular value. As such, the one or more mobile devicesqueried can be those located in the selected area of the network.

In some embodiments, the one or more mobile devices selected by thecommunication component 200 can be those meeting the fundamental set ofcriteria, and having an AGPS return success rate of a predeterminedvalue.

In some embodiments, the one or more mobile devices selected by thecommunication component 200 can be those meeting the fundamental set ofcriteria, and currently in need of calibration.

In some embodiments, only mobile devices associated with a selectedsubscriber (e.g., AT&T subscriber), having AGPS capability, on an activecall and having a historical call duration within a predetermined timerange are selected by the communication component 200. The mobiledevices that meet such criteria can be prioritized by the communicationcomponent 200 based, at least, on one or more other criteria. Forexample, the mobile devices can be prioritized for selection based onthe area of the network in which the mobile devices are located, anumber of TMs for the mobile devices, the AGPS return success rateand/or the current signal strengths of the mobile devices.

Turning back to the antenna location determination system 116′ of FIG.2, the data storage 210 can be configured to store informationtransmitted to, received by and/or processed by the antenna locationdetermination system 116′. In various embodiments, the data storage 210can store information identifying mobile devices selected for query bythe communication component 200, TCELL information, AGPS information,information test antenna locations and/or estimated antenna location. Invarious embodiments, TCELL information can include chip offsetinformation associated with BS radios. The BS can be associated with themobile devices.

The memory 206 can be a computer-readable storage medium storingcomputer-executable instructions and/or information for performing thefunctions described herein with reference to the antenna locationdetermination system 116′. Processor 208 can perform one or more of thefunctions described herein with reference to the antenna locationdetermination system 116′. In some embodiment, the processor 208 canperform the one or more functions based on computer-executableinstructions stored in the memory 206.

The aggregation component 202 can aggregate the measurement information,or portions thereof, received from the mobile devices. In variousembodiments, the aggregation component 202 can aggregate the informationover a period of hours, days, weeks, months and/or years. As such, insome embodiments, the measurement information employed for theestimation of the antenna locations can be aggregated measurementinformation.

The computation component 204 can compute one or more estimated antennalocations. In some embodiments, the estimated antenna locations can bethe locations of co-located antennas 106, 107 described with referenceto FIG. 1. In some embodiments, the estimated antenna locations arecomputed based on measured AGPS information, and stored TCELL values,for the mobile devices transmitting the AGPS information to the antennalocation determination system 116′.

The computation component 204 of the antenna location determinationsystem 116′ will now be described in more detail with reference to theremaining figures. Turning first to FIGS. 3 and 4, FIG. 3 illustratesanother example system that can be employed to facilitate determinationof antenna location. FIG. 4 illustrates an example data storage thatfacilitates determination of antenna location. The computation component204′ can include one or more of the structure and/or functionality ofthe computation component 204 described with reference to FIG. 2 (andvice versa).

The computation component 204′ can include an observed time difference(OTD) component 302, common radio offset component 304, path delaycomponent 306, real time difference (RTD) component 308, outlierdetermination component 310, test and estimated antenna location (TEAL)component 312, memory 314, processor 316 and/or data storage 318. Invarious embodiments, one or more of the OTD component 302, common radiooffset component 304, path delay component 306, RTD component 308,outlier determination component 310, TEAL component 312, memory 314,processor 316 and/or data storage 318 can be electrically and/orcommunicatively coupled to one or another to perform one or more of thefunctions of computation component 204′.

The OTD component 302 can compute the observed time difference betweenBS radios (e.g., BS radios i and j). The BS radios can be associatedwith mobile devices from which AGPS information is received. In variousembodiments, the OTD can be derived from the AGPS information receivedfrom the mobile devices. For example, the OTD component 302 canaccumulate OTD values from RRC measurement reports received from themobile devices transmitting AGPS information. RRC measurement reportinformation 410 can be stored in data storage 318′. The OTD values canbe stored as OTD information 402 in the data storage 318′.

The common radio offset component 304 can compute a chip offset betweena pair of BS radios (e.g., BS radios i and j). In various embodiments, afirst BS radio (e.g., BS radio i) for a specific sector can have anoffset of 0 while a second BS radio (e.g., BS radio j) for the sectorcan have an offset of 1. In various embodiments, the offset can be theTCELL value for the BS radio for the sector. In this instance, forexample, the TCELL values can be 0 and 1, respectively. The chip offsetcan equal the difference between the offsets, or can be equal to 1. Eachchip offset can correspond to 256 chips. As such, a chip offset of 1 cancorrespond to 256 chips. However, in various embodiments, the offset cancorrespond to a different number of chips (e.g., an offset of 1corresponding to 260 chips). In such instances, the difference of 4chips can imply antenna location that has not been properly determinedand/or accounted for. The antenna location determination system 116 canemploy the offset information to increase the likelihood of estimatingthe actual antenna location. The chip offset can be or be included asthe common radio offset information 408 stored in the data storage 318′.

In various embodiments, if the BS radios are associated with cellsectors having known and significant radio frequency (RF) cable delaydifferences between the BS radios and the cell antenna input ports, anoffset table can be predetermined for the cell sector. In otherembodiments, the cable delays between the BS radios and the cell sectorantenna inputs can be assumed to be equal for all BS radios in a cellsector.

The path delay component 306 can compute the path delay between signalsreceived from a pair of mobile devices from which the AGPS informationis received. The path delay can be or be included within the path delayinformation 404 stored in the data storage 318′.

The RTD component 308 can compute the transmission time offset betweentwo BSs associated with the co-located antennas. The transmission timeoffset can be included in the real-time difference information 406stored in data storage 318′.

The TEAL component 312 can compute test antenna locations and determineestimated antenna locations. In some embodiments, the estimated antennalocations can be determined based on the computed test antennalocations, chip offset values and/or the OTD values.

With reference to FIGS. 2 and 3, in some embodiments, the TEAL component312 can receive and/or process information associated with a first setof mobile devices selected by the communication component 200 to provideAGPS information. For example, the TEAL component 312 can receive theOTD values received from the mobile devices. The OTD values can beprocessed by the OTD component 302 and output to the TEAL component 312.The TEAL component 312 can also process the chip offset information(e.g., TCELL values).

In some embodiments, the TEAL component 312 for a pair of mobile devices108, 110 can employ Equation (1) in computing the estimated antennalocation. For example, Equation 1 can be:OTD_(ij)−(TCELL value_(j) −TCELL value_(i))=D _(ij) =D _(i) −D _(j)  (1)where OTD_(ij) can be the OTD between BS radio i and BS radio j, TCELLvalue_(j) can be the TCELL value (or chip offset) associated with BSradio j, TCELL value, can be the TCELL value (or chip offset) associatedwith BS radio i, D_(i) can be the distance from the mobile device i toantenna i, D_(j) can be the distance from the mobile device j to antennaj and D_(ij) can be the path delay once the RTD is removed from theOTD_(ij).

The TEAL component 312 can determine a first set of test antennalocations associated with the first set of mobile devices. In someembodiments, the test antenna locations can be stored in the antennalocation information 412 in data storage 318′. In some embodiments, foreach AGPS received from a mobile device within the first set of mobiledevices, the TEAL component 312 assumes a test antenna location. Theassumed test location can be assumed based on the AGPS informationreceived from a mobile device.

The TEAL component 312 can compute a first set of distances between themobile device and the test antenna location. For example, for an assumedtest antenna location, the TEAL component 312 can compute a distancefrom the assumed test location to the mobile device providing the AGPSfrom which the assumed test location was derived.

The TEAL component 312 can compute a second set of distances from asecond test antenna location to the location of mobile devices within asecond set of mobile devices.

The TEAL component 312 can determine the test antenna location in thesecond set of test antenna locations that has the lowest error. In someembodiments, the test antenna location can have an error that is lowerthan an error associated with another test antenna location in thesecond set of test antenna locations. The test antenna location in thesecond set of test antenna locations that has the lowest error (or, insome embodiments, has a lower error) can be the estimated antennalocation.

In some embodiments, the TEAL component 312 can determine the estimatedBS antenna location and/or the relative distances between BS antennalocations periodically. For example, the determination can be madeweekly in some embodiments.

While the description discloses a first set of mobile devices, in someembodiments, the first set of mobile devices can include only a singlemobile device, while in other embodiments, the first set of mobiledevices can include any number of mobile devices selected by thecommunication component 200 for submission of AGPS information to theantenna location determination system 116′. Also, in variousembodiments, the number of mobile devices in the first set of mobiledevices can change as different mobile devices can be aggregated and/orremoved based on whether the mobile devices meet the criteria forselection, whether antenna location estimates need to be updated or thelike.

The outlier determination component 310 can determine and/or filter outoutlier values computed in the process of determining the estimatedantenna locations. In some embodiments, the outlier values can be thoseinfluenced by repeater delay. For example, since a repeater in thenetwork receives a radio signal from a mobile device and re-broadcaststhat signal, increased signal time delay can result as the signal iscaptured, processed, and re-transmitted. This signal time delay cancause a signal received at the antenna location determination system toappear to be a signal transmitted from a distance greater than theactual distance from which the signal was transmitted.

To determine signals having delay resultant from the presence ofsignals, the outlier determination component 310 can employ time delaymapping across the coverage area of the co-located antennas. Thosesignals that are received with delay that is greater than an expectedvalue can be identified as outliers and the signals and/or the possibleantenna location calculated based on the signal, can be filtered. Forexample, in various embodiments, the outlier determination component canemploy interquartile filtering to identify outlier values and can filterout such values. Interquartile filtering can employ an interquartilerange, which is a measure of statistical dispersion across a group ofdata points (e.g., possible antenna locations). The interquartile rangecan be the difference between the upper and lower quartiles of datapoints.

In some embodiments, the outlier determination component 310 can removeone or more test antenna locations that are outliers prior tocomputation of the first set of distances by the TEAL component 312. Insome embodiments, the outlier determination component 310 can remove oneor more of the second set of distances that are outliers prior tocomputation of the second set of distances by the TEAL component 312.

In some embodiments, the outlier determination component 310 can alsoidentify when signals are received with significant time delays from thetime that the AGPS request is made. In various embodiments, thesesignals can also be filtered out and/or the mobile device from which thesignals were received can be identified so that subsequent AGPS requestsare not transmitted to the mobile device.

The memory 314 can be a computer-readable storage medium storingcomputer-executable instructions and/or information for performing thefunctions described herein with reference to the antenna locationdetermination system 116′. Processor 316 can perform one or more of thefunctions described herein with reference to the antenna locationdetermination system 116′.

The data storage 318 can be configured to store information transmittedto, received by and/or processed by the computation component 204′. Invarious embodiments, the data storage 318 can store informationidentifying mobile devices selected for query by the communicationcomponent 200, OTD values, RTD values, common radio offset information,test antenna locations, estimated antenna locations, path delayinformation, and the like. In some embodiments, the data storage 318 caninclude the information described with reference to data storage 318′ ofFIG. 4.

FIGS. 5-9 illustrate example flowcharts of methods that facilitatedetermination of antenna location.

Turning first to FIG. 5, at 502, method 500 can include collecting, by asystem including at least one processor, measurement information from aplurality of mobile devices dispersed over a geographical region. Insome embodiments, the measurement information can include location andtiming information for the plurality of mobile devices. The system canbe the antenna location determination system 116, 116′ in someembodiments.

At 504, method 500 can include computing, by the system, a timingdifference between co-located antennas of a BS associated with theplurality of mobile devices.

At 506, method 500 can include determining, by the system, a location ofa first one of the co-located antennas and a location of a second one ofthe co-located antennas. In some embodiments, the determination can bebased, at least, on a plurality of test locations of the second one ofthe co-located antennas and errors associated with the plurality of testlocations.

In some embodiments, determining the location of the first one of theco-located antennas and the location of the second one of the co-locatedantennas can include evaluating a plurality of areas circumscribing theplurality of test locations. Then, a plurality of first distancesbetween a plurality of mobile devices and respective plurality of testlocations can be assigned.

A plurality of second distances between the plurality of mobile devicesand estimated locations of the second one of the co-located antennas canbe determined. The estimated locations of the second one of theco-located antennas can be based on the plurality of first distances.

A plurality of errors between the plurality of second distances and theplurality of test locations can be determined. The errors can be rootmean square errors in some embodiments.

One of the plurality of second distances corresponding to the leasterror can be determined. The location of the second one of theco-located antennas can also be determined to be the one of theplurality of second distances corresponding to the least one of theplurality of errors. Further, the location of the first one of theco-located antennas can be determined to be the one of the plurality oftest locations employed to compute the one of the plurality of seconddistances corresponding to the least one of the plurality of errors.

Turning now to FIG. 6, at 602, method 600 can include receivingmeasurement information from a plurality of mobile devices associatedwith co-located antennas. In various embodiments, the measurementinformation can be aggregated from the mobile devices over a period ofhours, days, weeks, months and/or years.

In some embodiments, the measurement information can include AGPSinformation. In some embodiments, the AGPS information can be receivedfrom mobile devices selected according to various criteria. By way ofexample, but not limitation, in some embodiments, an AGPS query can besent to mobile devices that are associated with a particular subscriberand that have AGPS capability. In some embodiments, the AGPS query canbe sent to mobile devices that are also currently involved in an activecall and that have a historical call duration time within a particulartime range (e.g., between approximately 10 and 40 seconds).

At 604, method 600 can include determining at least one estimated BSantenna location. The estimated BS antenna location can be based on themeasurement information. In one embodiment, the determination of theestimated BS antenna location can be as described with reference to FIG.7.

Turning now to FIG. 7, at 702, method 700 can include selecting at leasttwo pairs of the plurality of the mobile devices associated withreceived AGPS information. For example, from a number of differentmobile devices, mobile devices can be paired with one another. In oneembodiment, two mobile devices are associated as a first pair and twoother mobile devices are associated as a second pair. In otherembodiments, one or more of the mobile devices in the pairs can be thesame. For example, a first mobile device can be associated with a secondmobile device to create a first pair, and the first mobile device can beassociated with a third mobile device to create a second pair.

At 704, method 700 can include determining respective chip offsetsbetween BS radios associated with pairs of the at least two pairs of theplurality of mobile devices. In some embodiments, the chip offsetsbetween the BS radios can be the difference between the TCELL valueassociated with a first BS radio (e.g., BS radio i) and the TCELL valueassociated with a second BS radio (e.g., BS radio j).

At 706, method 700 can include determining respective OTDs between BSradios associated with at least two pairs of the plurality of mobiledevices. The respective OTDs can be derived from the AGPS informationfrom the at least two pairs of the plurality of the mobile devices.

At 708, method 700 can include computing the estimated BS antennalocation based, at least, on the respective chip offsets and therespective OTDs. For example, in some embodiments, the estimated BSantenna location, D_(j), can be determined based on Equation (2) belowO _(ji)−(TCELL_(j) −TCELL_(i))=D _(ij) =D _(i) −D _(j)  (2)in which OTD_(ij) can be the OTD between BS radio i and BS radio j,TCELL value_(j) can be the TCELL value (or chip offset) associated withBS radio j, TCELL value_(i) can be the TCELL value (or chip offset)associated with BS radio i, D_(i) can be the distance from the mobiledevice i to antenna i (which can be a test antenna location), D_(j) canbe the distance from the mobile device j to antenna j (which can be theestimated antenna location) and D_(ij) can be the path delay once theRTD is removed from the OTD_(ij).

In various embodiments, computing the estimated antenna location can beperformed as described with reference to FIG. 8.

At 802, method 800 can include determining a first set of test antennalocations associated with a first set of mobile devices of the at leasttwo pairs of the plurality of the mobile devices. The first set of testantenna locations can be derived from respective AGPS informationreceived from the first set of mobile devices.

At 804, method 800 can include computing a first set of distances fromthe first set of mobile devices to the first set of test antennalocations associated with respective ones of the first set of the mobiledevices.

At 806, method 800 can include computing a second set of distances froma second set of mobile devices of the at least two pairs of theplurality of mobile devices to respective ones of the second set of testantenna locations for the second set of mobile devices.

At 808, method 800 can include computing respective errors for therespective second set of test antenna locations. In various embodiments,the errors can be root mean square errors.

At 810, method 800 can include determining one of the second set of testantenna locations having a lower error than another one of therespective second set of test antenna locations, wherein the one of thesecond set of test antenna locations having the lower error is the atleast one estimated antenna location. In some embodiments, the one ofthe second set of test antenna locations having the lowest error of theerrors for the second set of test antenna locations is the at least oneestimated antenna location.

Turning to FIG. 9, at 902, method 900 can include determining a firstset of test antenna locations associated with a first set of mobiledevices. The first set of test antenna locations can be derived fromrespective AGPS information received from the first set of the mobiledevices.

At 904, method 900 can include removing at least one of the first set oftest antenna locations. The test antenna location can be removed basedon a determination that the test antenna location that is determined in902 is influenced by a repeater delay.

At 906, method 900 can include removing at least one of a second set oftest antenna locations. The second set of test antenna locations can bederived based on the first test antenna locations and the second set ofmobile devices generating AGPS information. The test antenna locationcan be removed based on a determination that the test antenna locationthat is determined is influenced by a repeater delay.

At 908, method 900 can include computing respective errors for thesecond set of test antenna locations. In some embodiments, the errorscan be root mean square errors.

At 910, method 900 can include determining a one of the second set oftest antenna locations having the lowest error as the estimated antennalocation.

In some embodiments, antenna location is estimated in latitude andlongitude. Once antenna location is estimated, a subset of the AGPSlocation information can be employed to estimate the antenna heights. Insome embodiments, for example, pairs of antenna heights can beiteratively tested around database-provided values to hone in on thebest fit to the dataset.

In some embodiments, the mobile device can be assumed to be limited tobe no closer than 10 times the antenna height above ground level. Insome embodiments, the great circle or haversine formula can be employedto calculate distance.

In various embodiments, a selected number of RANAP/AGPS values and aselected set of most recently-received RRC_MR information can be stored.Old values can be flushed out in a first in first out fashion in someembodiments. Accordingly, antenna location changes can be determinedbased on re-computations of antenna locations performed when newRANAP/AGPS values and/or RRC measurement report information is received.

Referring now to FIG. 10, there is illustrated a block diagram of acomputer operable to facilitate antenna location determination. Forexample, in some embodiments, the computer can be or be included withinthe antenna location determination system 116, 116′.

In order to provide additional context for various embodiments of theembodiments described herein, FIG. 10 and the following discussion areintended to provide a brief, general description of a suitable computingenvironment 1000 in which the various embodiments of the embodimentdescribed herein can be implemented. While the embodiments have beendescribed above in the general context of computer-executableinstructions that can run on one or more computers, those skilled in theart will recognize that the embodiments can be also implemented incombination with other program modules and/or as a combination ofhardware and software.

Generally, program modules include routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the inventive methods can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices.

The illustrated embodiments of the embodiments herein can be alsopracticed in distributed computing environments where certain tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules can be located in both local and remote memory storage devices.

Computing devices typically include a variety of media, which caninclude computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structured dataor unstructured data. Computer-readable storage media can include, butare not limited to, random access memory (RAM), read only memory (ROM),electrically erasable programmable read only memory (EEPROM), flashmemory or other memory technology, compact disk read only memory(CD-ROM), digital versatile disk (DVD) or other optical disk storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices or other tangible and/or non-transitory mediawhich can be used to store desired information. Computer-readablestorage media can be accessed by one or more local or remote computingdevices, e.g., via access requests, queries or other data retrievalprotocols, for a variety of operations with respect to the informationstored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and includes any information deliveryor transport media. The term “modulated data signal” or signals refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in one or more signals. By wayof example, and not limitation, communication media include wired media,such as a wired network or direct-wired connection, and wireless mediasuch as acoustic, RF, infrared and other wireless media.

With reference again to FIG. 10, the example environment 1000 forimplementing various embodiments of the aspects described hereinincludes a computer 1002, the computer 1002 including a processing unit1004, a system memory 1006 and a system bus 1008. The system bus 1008couples system components including, but not limited to, the systemmemory 1006 to the processing unit 1004. The processing unit 1004 can beany of various commercially available processors. Dual microprocessorsand other multi-processor architectures can also be employed as theprocessing unit 1004.

The system bus 1008 can be any of several types of bus structure thatcan further interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 1006includes ROM 1010 and RAM 1012. A basic input/output system (BIOS) canbe stored in a non-volatile memory such as ROM, erasable programmableread only memory (EPROM), EEPROM, which BIOS contains the basic routinesthat help to transfer information between elements within the computer1002, such as during startup. The RAM 1012 can also include a high-speedRAM such as static RAM for caching data.

The computer 1002 further includes an internal hard disk drive (HDD)1014 (e.g., EIDE, SATA), which internal hard disk drive 1014 can also beconfigured for external use in a suitable chassis (not shown), amagnetic floppy disk drive (FDD) 1016, (e.g., to read from or write to aremovable diskette 1018) and an optical disk drive 1020, (e.g., readinga CD-ROM disk 1022 or, to read from or write to other high capacityoptical media such as the DVD). The hard disk drive 1014, magnetic diskdrive 1016 and optical disk drive 1020 can be connected to the systembus 1008 by a hard disk drive interface 1024, a magnetic disk driveinterface 1026 and an optical drive interface 1028, respectively. Theinterface 1024 for external drive implementations includes at least oneor both of Universal Serial Bus (USB) and Institute of Electrical andElectronics Engineers (IEEE) 1094 interface technologies. Other externaldrive connection technologies are within contemplation of theembodiments described herein.

The drives and their associated computer-readable storage media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 1002, the drives andstorage media accommodate the storage of any data in a suitable digitalformat. Although the description of computer-readable storage mediaabove refers to a hard disk drive (HDD), a removable magnetic diskette,and a removable optical media such as a CD or DVD, it should beappreciated by those skilled in the art that other types of storagemedia which are readable by a computer, such as zip drives, magneticcassettes, flash memory cards, cartridges, and the like, can also beused in the example operating environment, and further, that any suchstorage media can contain computer-executable instructions forperforming the methods described herein.

A number of program modules can be stored in the drives and RAM 1012,including an operating system 1030, one or more application programs1032, other program modules 1034 and program data 1036. All or portionsof the operating system, applications, modules, and/or data can also becached in the RAM 1012. The systems and methods described herein can beimplemented utilizing various commercially available operating systemsor combinations of operating systems.

A user can enter commands and information into the computer 1002 throughone or more wired/wireless input devices, e.g., a keyboard 1038 and apointing device, such as a mouse 1040. Other input devices (not shown)can include a microphone, an infrared (IR) remote control, a joystick, agame pad, a stylus pen, touch screen or the like. These and other inputdevices are often connected to the processing unit 1004 through an inputdevice interface 1042 that can be coupled to the system bus 1008, butcan be connected by other interfaces, such as a parallel port, an IEEE1394 serial port, a game port, a universal serial bus (USB) port, an IRinterface, etc.

A monitor 1044 or other type of display device can be also connected tothe system bus 1008 via an interface, such as a video adapter 1046. Inaddition to the monitor 1044, a computer typically includes otherperipheral output devices (not shown), such as speakers, printers, etc.

The computer 1002 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 1048. The remotecomputer(s) 1048 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallyincludes many or all of the elements described relative to the computer1002, although, for purposes of brevity, only a memory/storage device1050 is illustrated. The logical connections depicted includewired/wireless connectivity to a local area network (LAN) 1052 and/orlarger networks, e.g., a wide area network (WAN) 1054. Such LAN and WANnetworking environments are commonplace in offices and companies, andfacilitate enterprise-wide computer networks, such as intranets, all ofwhich can connect to a global communications network, e.g., theInternet.

When used in a LAN networking environment, the computer 1002 can beconnected to the local network 1052 through a wired and/or wirelesscommunication network interface or adapter 1056. The adapter 1056 canfacilitate wired or wireless communication to the LAN 1052, which canalso include a wireless AP disposed thereon for communicating with thewireless adapter 1056.

When used in a WAN networking environment, the computer 1002 can includea modem 1058 or can be connected to a communications server on the WAN1054 or has other means for establishing communications over the WAN1054, such as by way of the Internet. The modem 1058, which can beinternal or external and a wired or wireless device, can be connected tothe system bus 1008 via the input device interface 1042. In a networkedenvironment, program modules depicted relative to the computer 1002 orportions thereof, can be stored in the remote memory/storage device1050. It will be appreciated that the network connections shown areexample and other means of establishing a communications link betweenthe computers can be used.

The computer 1002 can be operable to communicate with any wirelessdevices or entities operatively disposed in wireless communication,e.g., a printer, scanner, desktop and/or portable computer, portabledata assistant, communications satellite, any piece of equipment orlocation associated with a wirelessly detectable tag (e.g., a kiosk,news stand, restroom), and telephone. This can include Wireless Fidelity(Wi-Fi) and BLUETOOTH® wireless technologies. Thus, the communicationcan be a predefined structure as with a conventional network or simplyan ad hoc communication between at least two devices.

Wi-Fi can allow connection to the Internet from a couch at home, a bedin a hotel room or a conference room at work, without wires. Wi-Fi is awireless technology similar to that used in a cell phone that enablessuch devices, e.g., computers, to send and receive data indoors and out;anywhere within the range of a base station. Wi-Fi networks use radiotechnologies called IEEE 802.11(a, b, g, n, etc.) to provide secure,reliable, fast wireless connectivity. A Wi-Fi network can be used toconnect computers to each other, to the Internet, and to wired networks(which can use IEEE 802.3 or Ethernet). Wi-Fi networks operate in theunlicensed 2.4 and 5 GHz radio bands, at an 11 Mbps (802.11a) or 54 Mbps(802.11b) data rate, for example or with products that contain bothbands (dual band), so the networks can provide real-world performancesimilar to the basic 10BaseT wired Ethernet networks used in manyoffices.

The embodiments described herein can employ artificial intelligence (AI)to facilitate automating one or more features described herein. Theembodiments (e.g., in connection with automatically identifying acquiredcell sites that provide a maximum value/benefit after addition to anexisting communication network) can employ various AI-based schemes forcarrying out various embodiments thereof. Moreover, the classifier canbe employed to determine a ranking or priority of the each cell site ofthe acquired network. A classifier is a function that maps an inputattribute vector, x=(x1, x2, x3, x4, . . . , xn), to a confidence thatthe input belongs to a class, that is, f(x)=confidence(class). Suchclassification can employ a probabilistic and/or statistical-basedanalysis (e.g., factoring into the analysis utilities and costs) toprognose or infer an action that a user desires to be automaticallyperformed. A support vector machine (SVM) is an example of a classifierthat can be employed. The SVM operates by finding a hypersurface in thespace of possible inputs, which the hypersurface attempts to split thetriggering criteria from the non-triggering events. Intuitively, thismakes the classification correct for testing data that is near, but notidentical to training data. Other directed and undirected modelclassification approaches include, e.g., naïve Bayes, Bayesian networks,decision trees, neural networks, fuzzy logic models, and probabilisticclassification models providing different patterns of independence canbe employed. Classification as used herein also is inclusive ofstatistical regression that is utilized to develop models of priority.

As will be readily appreciated, one or more of the embodiments canemploy classifiers that are explicitly trained (e.g., via a generictraining data) as well as implicitly trained (e.g., via observing UEbehavior, operator preferences, historical information, receivingextrinsic information). For example, SVMs can be configured via alearning or training phase within a classifier constructor and featureselection module. Thus, the classifier(s) can be used to automaticallylearn and perform a number of functions, including but not limited todetermining according to a predetermined criteria which of the acquiredcell sites will benefit a maximum number of subscribers and/or which ofthe acquired cell sites will add minimum value to the existingcommunication network coverage, etc.

As employed herein, the term “processor” can refer to substantially anycomputing processing unit or device comprising, but not limited tocomprising, single-core processors; single-processors with softwaremultithread execution capability; multi-core processors; multi-coreprocessors with software multithread execution capability; multi-coreprocessors with hardware multithread technology; parallel platforms; andparallel platforms with distributed shared memory. Additionally, aprocessor can refer to an integrated circuit, an application specificintegrated circuit (ASIC), a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), a programmable logic controller (PLC), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components or any combination thereof designedto perform the functions described herein. Processors can exploitnano-scale architectures such as, but not limited to, molecular andquantum-dot based transistors, switches and gates, in order to optimizespace usage or enhance performance of user equipment. A processor canalso be implemented as a combination of computing processing units.

As used herein, terms such as “data storage,” data storage,” “database,”and substantially any other information storage component relevant tooperation and functionality of a component, refer to “memorycomponents,” or entities embodied in a “memory” or components comprisingthe memory. It will be appreciated that the memory components orcomputer-readable storage media, described herein can be either volatilememory or nonvolatile memory or can include both volatile andnonvolatile memory.

Memory disclosed herein can include volatile memory or nonvolatilememory or can include both volatile and nonvolatile memory. By way ofillustration, and not limitation, nonvolatile memory can include readonly memory (ROM), programmable ROM (PROM), electrically programmableROM (EPROM), electrically erasable PROM (EEPROM) or flash memory.Volatile memory can include random access memory (RAM), which acts asexternal cache memory. By way of illustration and not limitation, RAM isavailable in many forms such as static RAM (SRAM), dynamic RAM (DRAM),synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhancedSDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).The memory (e.g., data storages, databases) of the embodiments areintended to comprise, without being limited to, these and any othersuitable types of memory.

What has been described above includes mere examples of variousembodiments. It is, of course, not possible to describe everyconceivable combination of components or methodologies for purposes ofdescribing these examples, but one of ordinary skill in the art canrecognize that many further combinations and permutations of the presentembodiments are possible. Accordingly, the embodiments disclosed and/orclaimed herein are intended to embrace all such alterations,modifications and variations that fall within the spirit and scope ofthe appended claims. Furthermore, to the extent that the term “includes”is used in either the detailed description or the claims, such term isintended to be inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. A method, comprising: collecting, by a systemcomprising at least one processor, measurement information from mobiledevices dispersed over a geographical region, wherein the measurementinformation comprises location and timing information for the mobiledevices; determining, by the system, a timing difference betweenco-located antennas of a base station device associated with the mobiledevices; determining, by the system, a first location of a first one ofthe co-located antennas of the base station device and a second locationof a second one of the co-located antennas of the base station device,based, at least, on test locations of the second one of the co-locatedantennas of the base station device and a first set of errors associatedwith the test locations, wherein the determining the first location andthe second location comprises: determining first distances between themobile devices and an estimated location of the second one of theco-located antennas; determining a second set of errors between thefirst distances and the test locations; and determining that the secondlocation of the second one of the co-located antennas corresponds to oneof the first distances that has a value satisfying a defined function ofthe second set of errors.
 2. The method of claim 1, wherein theestimated location of the second one of the co-located antennas is basedon second distances, and wherein the second distances comprise distancesbetween the mobile devices and respective test locations of the testlocations.
 3. The method of claim 1, wherein the second set of errorsare root mean square errors.
 4. The method of claim 1, furthercomprising aggregating, by the system, the measurement information,wherein the aggregating is over a period of time.
 5. The method of claim4, wherein the period of time is a number of hours.
 6. The method ofclaim 4, wherein the period of time is a number of days.
 7. The methodof claim 1, further comprising: determining that the location of thefirst one of the co-located antennas corresponds to the one of the testlocations that corresponds to the one of the first distances resultingin the defined function being satisfied, wherein the defined function issatisfied by a least value for the second set of errors.
 8. Anon-transitory computer-readable storage medium storingcomputer-executable instructions that, in response to execution, cause asystem comprising a processor to perform operations, comprising:collecting measurement information from mobile devices; and determininga location of a first one of co-located antennas of a base stationdevice and a location of a second one of co-located antennas of the basestation device, based, at least, on test locations of the second one ofthe co-located antennas of the base station device and a first set oferror information associated with the test locations, wherein thedetermining the location comprises: determining first distances betweenthe mobile devices and an estimated location of the second one of theco-located antennas; and determining that the location of the second oneof the co-located antennas corresponds to one of the first distancesthat has a value satisfying a defined function of the second set oferror information, wherein the second set of error information isassociated with errors between the first distances and the testlocations.
 9. The non-transitory computer-readable storage medium ofclaim 8, wherein the estimated location of the second one of theco-located antennas is based on second distances, and wherein the seconddistances comprise distances between the mobile devices and respectivetest locations of the test locations.
 10. The non-transitorycomputer-readable storage medium of claim 8, wherein the operationsfurther comprise: determining that the location of the first one of theco-located antennas corresponds to the one of the test locations thatcorresponds to the one of the first distances resulting in the definedfunction being satisfied, wherein the defined function determines aleast value for the second set of error information.
 11. Thenon-transitory computer-readable storage medium of claim 8, wherein thesecond set of error information comprises root mean square errors. 12.The non-transitory computer-readable storage medium of claim 8, whereinthe operations further comprise aggregating the measurement information,wherein the aggregating is over a period of time.
 13. The non-transitorycomputer-readable storage medium of claim 10, wherein the period of timeis a number of hours.
 14. The non-transitory computer-readable storagemedium of claim 10, wherein the period of time is a number of days. 15.A system, comprising: a processor; and a memory that stores executableinstructions that, when executed by the processor, facilitateperformance of operations, comprising: collecting measurementinformation from mobile devices; and determining a location of a firstone of co-located antennas of a base station device and a location of asecond one of co-located antennas of the base station device, based ontest locations of the second one of the co-located antennas of the basestation device and a first set of errors associated with the testlocations, wherein the determining the location comprises: determiningfirst distances between the mobile devices and an estimated location ofthe second one of the co-located antennas; determining a second set oferrors between the first distances and the test locations; anddetermining that the location of the second one of the co-locatedantennas corresponds to one of the first distances that has a valuesatisfying a defined function of the second set of errors.
 16. Thesystem of claim 15, wherein the estimated location of the second one ofthe co-located antennas is based, at least, on second distances, andwherein the second distances comprise distances between the mobiledevices and respective test locations of the test locations.
 17. Thesystem of claim 15, wherein the operations further comprise: determiningthat the location of the first one of the co-located antennascorresponds to the one of the test locations that corresponds to the oneof the first distances resulting in a least value for the second set oferrors.
 18. The system of claim 15, wherein the second set of errors areroot mean square errors.
 19. The system of claim 15, wherein theoperations further comprise aggregating the measurement information,wherein the aggregating is over a period of time.
 20. The system ofclaim 19, wherein the period of time is a number of hours.